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cs.LG2024
Improved Anomaly Detection through Conditional Latent Space VAE Ensembles
Oskar Åström, Alexandros Sopasakis
We propose a novel Conditional Latent space Variational Autoencoder (CL-VAE) to perform improved pre-processing for anomaly detection on data with known inlier classes and unknown…
cs.LG2024
Enhancing Carbon Emission Reduction Strategies using OCO and ICOS data
Oskar Åström, Carina Geldhauser, Markus Grillitsch +2
We propose a methodology to enhance local CO2 monitoring by integrating satellite data from the Orbiting Carbon Observatories (OCO-2 and OCO-3) with ground level observations from…